Nonlinear Filtering of Non-Gaussian Noise

Authors:
K. N. Plataniotis;D. Androutsos;A. N. Venetsanopoulos
Affiliations:
Department of Electrical and Computer Engineering, University of Toronto, Toronto, M5S 3G4, Canada. e-mail:kostas@dsp.toronto.edu;Department of Electrical and Computer Engineering, University of Toronto, Toronto, M5S 3G4, Canada. e-mail:kostas@dsp.toronto.edu;Department of Electrical and Computer Engineering, University of Toronto, Toronto, M5S 3G4, Canada. e-mail:kostas@dsp.toronto.edu
Venue:
Journal of Intelligent and Robotic Systems
Year:
1997

Citing 3
Cited 0

Introduction to statistical pattern recognition (2nd ed.)

Introduction to statistical pattern recognition (2nd ed.)
Distributed parallel processing state estimation algorithms

Distributed parallel processing state estimation algorithms
Signal Processing: Model Based Approach

Signal Processing: Model Based Approach

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper introduces a new nonlinear filter for a discrete time, linear system which is observed in additive non-Gaussian measurement noise. The new filter is recursive, computationally efficient and has significantly improved performance over other linear and nonlinear schemes. The problem of narrowband interference suppression in additive noise is considered as an important example of non-Gaussian noise filtering. It is shown that the new filter outperforms currently used approaches and at the same time offers simplicity in the design.